Quantum Principal Component Analysis

Quantum Principal Component Analysis is a quantum algorithm that extends the classical principal component analysis by leveraging quantum superposition and entanglement to exponentially accelerate the extraction of principal components from high-dimensional data encoded in quantum states.

31

Publications

3.8K

Citations

119

Authors

75

Institutions

Publications per year

2017–2026

24

Authors

119

  1. SL
    Seth Lloyd

    Massachusetts Institute of Technology, United States

    5 publications · 1.6K citations

    5

    h-index

  2. PR
    Patrick Rebentrost

    Massachusetts Institute of Technology, United States

    3 publications · 1.4K citations

    3

    h-index

  3. MM
    Masoud Mohseni

    Google (United States), United States

    3 publications · 1.9K citations

    3

    h-index

  4. HD
    Haitao Dong

    University of Oklahoma, United States

    2 publications · 63 citations

    2

    h-index

  5. PJ
    Patrick J. Coles

    Los Alamos National Laboratory, United States

    2 publications · 232 citations

    2

    h-index

1–5 of 119

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 184 citations

    4

    h-index

  2. Quantum Information Processing

    2 publications · 94 citations

    2

    h-index

  3. ChemPhysChem

    2 publications · 63 citations

    2

    h-index

  4. Physical Review Letters

    PRL · 2 publications · 201 citations

    2

    h-index

  5. npj Quantum Information

    1 publications · 206 citations

    1

    h-index

1–5